As low-field MRI technology is being disseminated into clinical settings around the world, it is important to assess the image quality required to properly diagnose and treat a given disease and evaluate the role of machine learning algorithms, such ...
BACKGROUND: Alzheimer's disease is a chronic neurodegenerative disease that destroys brain cells, causing irreversible degeneration of cognitive functions and dementia. Its causes are not yet fully understood, and there is no curative treatment. Howe...
Recent single-cell multimodal data reveal multi-scale characteristics of single cells, such as transcriptomics, morphology, and electrophysiology. However, integrating and analyzing such multimodal data to deeper understand functional genomics and ge...
In recent years, 2D convolutional neural networks (CNNs) have been extensively used to diagnose neurological diseases from magnetic resonance imaging (MRI) data due to their potential to discern subtle and intricate patterns. Despite the high perform...
Advances in experimental neuroscience have transformed our ability to explore the structure and function of neural circuits. At the same time, advances in machine learning have unleashed the remarkable computational power of artificial neural network...
The incidence of glioma is increasing year by year, seriously endangering people's health. Magnetic resonance imaging (MRI) can effectively provide intracranial images of brain tumors and provide strong support for the diagnosis and treatment of the ...
Humans and many animals have the ability to assess the confidence of their decisions. However, little is known about the underlying neural substrate and mechanism. In this study we propose a computational model consisting of a group of 'confidence ne...
In this paper, a model based on discrete wavelet transform and convolutional neural network for brain MR image classification has been proposed. The proposed model is comprised of three main stages, namely preprocessing, feature extraction, and class...
Depressive symptoms, feelings of sadness, anger, and loss that interfere with a person's daily life, are prevalent health concerns across populations that significantly result in adverse health outcomes with direct and indirect economic burdens at a ...
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